Pr Research 2Nd Half

Front 1

MBO

Back 1

management by objectives

process that matches a RACE or ROPE PR model

1. define problem (situation analysis)
2. state objectives (strategy)
3. create campaign or program that meets/surpasses objectives (implementation)
4. evaluate and provide feedback (assessment)

Front 2

ROI

Back 2

return on investment

an outcome variable that equates profit from investment

Front 3

RACE

Back 3

research
action
communication
evaluation

Front 4

ROPE

Back 4

research
objectives
programming
evaluation

Front 5

goals

Back 5

a general outcome expected when a campaign or program is completed; long term and gives direction

Front 6

objectives

Back 6

very specific and is based on projected and actual program outputs

specifically how to attain a goal and solve a problem

Cause and effect related

Front 7

3 kinds of objectives

Back 7

informational (what the target audience should know)
motivational (audience's attitude)
behavioral (outcome)

Front 8

characteristics of a "good" objective

Back 8

1. written with output, outtake, and outcome in mind
2. usually start with "to"
3. must include a measurable outcome (quantifiable)
4. in a campaign, start with informational, then motivational, then behavioral

Front 9

4 levels of measurement

Back 9

nominal
ordinal
interval
ratio

Front 10

advantages and disadvantages of nominal

Back 10

- classifcation of measured characteristic or attribute
- numbers assigned to categories
- mutually exclusive and collectively exhaustive

disadvantages: only qualitative; can't do advanced statistics or arithmatic operations

advantages: can show frequences and percentages

Front 11

ordinal

Back 11

- numbers used to rank categories
- description of order

disadvantage: unable to measure degree of difference between categories

Front 12

interval

Back 12

assumes distances between observations are equal along the continuum

disadvantage: no absolute zero so you can't do ratios

Front 13

ratio

Back 13

adds requirement of absolute zero point to continuum

can convert ratio to all other measurement levels

Front 14

categorical data

Back 14

puts observations into classes

nominal and ordinal measurements

advantages: simple to make
disadvantage: difficult to interpret

Front 15

continuous data

Back 15

assumes the distance between classes is equal and observation occurs on a continuum

interval and ratio

advantages: easy to explain; can reduce down to other measurement levels; offers more info
disadvantage: difficult to make

Front 16

validity

Back 16

Whether a measure is actually measuring what you defined it to measure

Front 17

four types of validy

Back 17

face
content
construct
criterion-related

Front 18

face validity

Back 18

occurs when you operationally define the measurement as measuring what you say it measures

based on your credibility

Front 19

content validity

Back 19

occurs when you ask experts to review your measure

based on authority and credibility of you and your judges

Front 20

construct validity

Back 20

obtained through an analysis of how the measure is actually used; statistical testing

Front 21

criterion-related validity

Back 21

established when your measure is shown to be related to other established measures or if it successfully predicts behavior; pretesting your measure against known measures to see if it can predict

Front 22

reliability

Back 22

the extent to which a series of measures yields results that are consistent and stable

Front 23

measurement scales

Back 23

- a composite measure of a concept
- for complex concepts that cannot be measured with a single item

likert
semantic differential

Front 24

likert scale

Back 24

how strongly they agree or disagree with a series of statements

- can calculate a summated/average score

(strongly disagree - strongly agree)

Front 25

semantial differential scale

Back 25

5, 7, or 9-point items bounded at each end by one of two bipolar ADJECTIVES

- can calculate a summated/average score

Front 26

7 steps in research process

Back 26

1. define research goal/objective
2. determine research design
3. determine data collection method
4. select sample
5. design data collection forms
6. collect data
7. analyze data reports

Front 27

3 stages in measurement process

Back 27

1. identify and define the concept
- conceptual definition (dictionary)
- operational definition (measurement)
2. determine how to measure an observable event
- level of measurement (nominal, ordinal, interval, ratio)
- scales (likert or semantic differential)
3. evaluate and revise
- reliability
- validity